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Find out in which ways do shopping centers vary as their size increase (determined by the number of shops).

Extracts from this document...

Introduction

Geography Coursework Min-Kai Lin 11AJP WJP Contents 1.Introduction 3 2.Data Presentation and Analysis 7 3.Conclusion 19 4.Evaluation 21 Introduction -Aim Shopping hierarchy exists in urban centers. The aim of this report is to find out in which ways do shopping centers vary as their size increase (determined by the number of shops). Research was carried out in Nei-Hu District, Taipei, Taiwan. The following were investigated: * Shop types * Building height * Traffic and pedestrian flow * Environmental quality-litter * Environmental quality-noise * Amenities * Shopping patterns: -Sphere of influence -Frequency of visit -Money spent -Transportation method -Purpose of visiting -Time spent 2 large centers where investigated. One was the local high street and another an out-of-town shopping center. The purpose was to find the difference between them. -The area and centers (see map for location of centers) Nei-Hu district is a mix of residential and business area. Taipei is a fairly new city, it may not have developed characteristics of older cities. It is located outer area of Taipei City. Thus, most people live here to commute to work. The results from different centers vary be due to its location. Two corner shops were investigated because there may not be enough respondents to show the characteristics of small centers. Centers were as follows: C1-main high street of the district C2-out of town shopping center C3-local high street C4-small center in residential area. C5-cluster of shops near high way. C6.1-corner shop C6.2-corner shop near commuting zone. At C1-C5, sample points were chosen to represent the area for certain data. See map. -Methodology At larger centers, sample points were chosen to represent the area. The larger the center, the more sample points were placed. This is because data may change in different parts of a large center. The points were random, but were equally spaced. * Shop Types This was done because as centers increase in size, shop types will change. The time of investigation is not important: shops are not likely to change. ...read more.

Middle

A desirable environment to shop is one of the reasons people visit out of town shopping centers. Within large centers, litter varies in different parts (see graph). Because shops cluster, in C1, [] has a high percentage of ploystyrene, plastic and drinks because restaurants/snacks cluster here. For C3, there is a fair distribution of shop types, causing litter to be more or less even. * Environmental quality-noise There is a weak correlation but it shows us the general trend is : as centers increase in size, noise worsens. This is mainly due to traffic flow. Large centers have higher traffic flow which causes noise. High pedestrian flow means chatter and shouting (common when a shop is on sale, a type of promotion from shop) contributes to noise. There are variations in large centers, but still following the trend. See map. * Shopping Patterns -Sphere of influence (see map) As you go up the shopping hierachy, the sphere of influence increases. Ideally SoI's should be circles, but because population is not evenly spread, and also there are obstrution such as mountains, airports and roads, SoI's are distorted. SoI's may not indicate the size of population served. SoI increase due to range. People are willing to travel further for higher order goods, which are located in large centers. This causes there to be less large centers and further apart: each serves a large area. As you go down the hierachy, there are more centers with smaller soi. This is becuase they provide more and more convinience goods, which only attract locals. There are 2 anomalies. C2's soi is slightly larger than C1. C2 only has 3 superstores and the majority of goods sold are convenience goods. It has gained a large soi becuase it is attracting people from further. Because it has good transportation links, it is very accessible and there are parking available. People visit here for weekly shopping for food. ...read more.

Conclusion

These results are biased towards these shoppers. Some points were more remote, thus the target number of respondents were not achieved. Also due to shop clustering at C2, and because there were many respondents from there, the results may be slightly biased. This means the results are not fair. One should have more sample points (evenly spread) to achieve accuracy. One would need to make sure chosen sample points do not affect the results too much. * Bi-Polar analysis There were many types of litter, which wasn't defined (e.g. metal). Using numbers of pieces of litter was unsuitable, it took too long to count. Solutions would be to take photographs of different levels of littering, and using this to judge centers. Noise was successful, as it corresponds with other data. However, duration was not included. At various points, the noise was loud but only lasted shortly; at others, it is the opposite. Noise levels should not be too well defined: this creates many exceptions. Also in C6, there was a construction site nearby which has affected the results. The true noise level may be lower. * Shop types, buildings heights, Amenities These were accurate, as they are not affected by time. However, human errors are inevitable, to prevent this, two or more people should count and confirm each other. I would include chain stores, because they tend to change with center size. * Data presentation It is not easy to see relationship between data; therefore it would be better to add scatter graphs linking different results. This result from this investigation is not very valid in answer to the question. It is only valid for Nei-Hu district. One would need to investigate different regions and countries; also carry out the observations every month over a year. More of the same data needs to be collected to ensure accuracy. More types of data can be collected to help explain, such as shops clustering, pollution and chain stores. However, the general trend agrees to the theory of urban shopping centers. Therefore this investigation is successful. ?? ?? ?? ?? 1 ...read more.

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